In class we’ve discussed in varying degrees whether or not Artificial Intelligence is already “smarter” than us. Calculators and Microsoft Excel Sheets can perform mathematical equations faster than humans could dream of solving them. Computers have been beating World Chess Champions since Deep Blue beat Kasparov in 1997 and have only been making improvements since. However, when it comes to what we value as “True Intelligence”, the stuff that helps us define our basis of human nature, it seems at times that there’s no way that a device like Siri or Google Home could be “smarter” than you.
Computers are programmable machines which can process massive amounts of information and perform logical equations using that data. They dominate in the quantitative space because according to Time Magazine, they are “not affected or influenced by emotions, feelings, wants, needs and other factors that often cloud the judgement and intelligence of us mere mortals”. Their pure computing power allows them to overcome natural human issues such as fatigue or memory capacity. Speed is where computers like IBM Watson excel. Watson diagnosed a patient with a rare form of Leukemia in less than 10 minutes using genetic data which normally would’ve taken 2 weeks by human experts. According to the leading researcher on the team, Watson did not catch something that wouldn’t have been caught by the doctors but the speed with which it was caught prevented complications and issues that arise quickly with forms of leukemia.
But what is true intelligence? The Jerusalem Post recognizes that people often misconstrue what artificial intelligence is and what some of the jargon used to describe these “smart” machines mean. Artificial Intelligence is the “ability to solve problems and learn”. Shlomo Maital elaborates, “Learning and problem solving are related. The more problems you solve, the more you learn. And the more you learn, the better you get at solving problems”. So if computers are able to learn from the previous information we feed it AND are able to discern new information each time it solves a problem, why don’t we feel that AI is taking over the world?
Machine learning is a subset of Artificial Intelligence which says that a set of computer algorithms will get better and better at solving issues with each solution it creates. For example, AI has been able to use camera footage to predict where Hamas rocket launchers will be set up and can name suspicious objects in camera footage. This information is relayed to a military unit for action to be taken. Another example is Waycare’s platform which uses machine learning and deep learning to predict traffic accidents about 2 hours before they occur. This allows police units to be dispatched to the area to reduce response time or to prevent accidents from happening. Both of these examples show that computers are able to predict things that may happen. These machines clearly are better at predicting when specific events may occur but still don’t cross that “cool/creepy” line.
Artificial Intelligence struggles with context and the “general knowledge” component of Intelligence. Phil Wainewright presents a great example of where artificial intelligence recognition sometimes ends up comparing apples to oranges and has trouble discerning when it’s doing this without specific instruction. Google, Amazon and Microsoft are able to digitally recognize and tag images with general tags like “ocean”, “nature”, and “water” but a company like Booking.com actually needs to know when looking at an image if there’s a “sea view” or if the room has a “balcony with a seating area”. While these services might be able to recognize objects individually, the machines originally weren’t able to recognize the context of the objects that were incorporated, something that most young/teenage adults could do easily. The article goes on to explain that it is the concept of new category creation and spontaneous knowledge building which claims to be the distinguishing factor of why Wainwright thinks that Humans will always be smarter than A.I.
Currently, Google Home and Amazon’s Alexa are flooding the country with social robots, able to interact as a physical representation of a digital friend. With different emphases, these robots aim to act as a digital personal assistant and complete certain tasks. While Siri seems to never want to cooperate with iPhone users, except when trying to text a friend or skip to the next song, some of these in home voice assistants have made some major strides in their conversation recognition and logic. Google home is the device which is leading the space in standalone quality and tends to be smarter than Amazon Echo according to Andrew Gebhart. Google Home is able to understand context of questions, something which Amazon has been playing catch up on recently. Google Home also is backed by none other than Google Search, an infinite treasure trove of information that needs to parsed by Google to be delivered in a conversational manner. Google also has voice recognition in its device, giving it the ability to deliver a catered answer to questions like “call my mom” or “what’s my calendar like today” rather than having to ask whom the device is speaking to…or avoiding accidentally calling your mother in law and not your mother (a hilarious example presented). I sure hope that the Amazon Echo doesn’t squash the development of a better base technology (Google Home) because it has better compatibility (cough…cough…VHS over BetaMax). Nevertheless, these devices are attempting to replicate what it feels like to have an assistant but their functionality is limited to the skills that are built. Unfortunately, having a conversation with an Amazon Alexa doesn’t feel conversational after the first time novelty wears off. The “social nature” of these devices still comes off as functional rather than dynamic and spontaneous.
I think lastly I would like to mention Jibo, a social robot whom I thought would change the way that the massive tech giants Google and Amazon thought about their smart speakers. Jibo boasted in its original Kickstarter that the little robot who stands about the height of a small lamp would be able to make video calls and read bedtime stories. Jibo appears to be a cute friend that sits on a nearby counter and a quick glance at a demo reveals just how lifelike and smooth his 360 Degree swivel movements are. Unfortunately, where the realism falls short is in Jibo’s functionality. Jibo is able to perform minor social tasks like telling you a joke, fun fact and even recognize you. However, Jibo is not able to answer your pondering questions or connect to calendars the same way that Google Home is able to. The connectivity and ecosystem of products is lacking for Jibo, so its knowledge is limited. Therefore, the promise of a truly social and fun robot to have around the house, the perfect roommmate, will just have to wait.
As we combine the ideas that Artificial Intelligence and Machine Learning can complete tasks better than we can with a social emphasis like Google Home and Amazon Alexa, maybe someday we will have a robot that “appears” to be truly smarter than us. But until robots “contextual awareness” and knowledge of infinite pattern recognition can improve, we will continue to create robots that feel like glorified automatons working towards tasks and not the recreation of iRobot.